77 citations · 273 across the 28 of their papers we have counts for
12 papers · 1 filter
WildClaims: Information Access Conversations in the Wild(Chat)
Hideaki Joko, Shakiba Amirshahi, Charles L. A. Clarke +1
The rapid advancement of Large Language Models (LLMs) has transformed conversational systems into practical tools used by millions. However, the nature and necessity of information…
LUMI: Unsupervised Intent Clustering with Multiple Pseudo-Labels
I-Fan Lin, Faegheh Hasibi, Suzan Verberne
In this paper, we propose an intuitive, training-free and label-free method for intent clustering in conversational search. Current approaches to short text clustering use LLM-gene…
LLMs Enable Bag-of-Texts Representations for Short-Text Clustering
I-Fan Lin, Faegheh Hasibi, Suzan Verberne
In this paper, we propose a training-free method for unsupervised short text clustering that relies less on careful selection of embedders than other methods. In customer-facing ch…
Towards a Large Physics Benchmark
Kristian G. Barman, Sascha Caron, Faegheh Hasibi +5
We introduce a benchmark framework developed by and for the scientific community to evaluate, monitor and steer large language model development in fundamental physics. Building on…
PromptAug: Fine-grained Conflict Classification Using Data Augmentation
Oliver Warke, Joemon M. Jose, Faegheh Hasibi +1
Given the rise of conflicts on social media, effective classification models to detect harmful behaviours are essential. Following the garbage-in-garbage-out maxim, machine learnin…
Why Uncertainty Estimation Methods Fall Short in RAG: An Axiomatic Analysis
Heydar Soudani, Evangelos Kanoulas, Faegheh Hasibi
Large Language Models (LLMs) are valued for their strong performance across various tasks, but they also produce inaccurate or misleading outputs. Uncertainty Estimation (UE) quant…